Responsible AI in Science
Privacy, citations, and integrity when you use AI
How to use AI responsibly in research — what happens to your data, how far to trust the output, and how to stay reproducible. Compares Claude, ChatGPT, and Gemini on the criteria a scientist must care about.
After this chapter you can
0/3 courses done — a course counts as done once you've finished all its lessons
| Feature | |||
|---|---|---|---|
| Videos tutorials on YouTube | ▶ 2 | ▶ 2 | ▶ 3 |
| Detailed course hands-on lessons & templates | Open → | Open → | Open → |
| Animated walkthrough watch each lesson play out | ▶ | ▶ | ▶ |
| One-click opt-out of training stop your chats training the model | ✓ | ✓ | ✓ |
| Safe for confidential data (free tier) before you opt out / upgrade | ◐ | ◐ | ✗ |
| EU / data-residency option keep data in a chosen region | ◐ | ✓ | ✓ |
| Inline source citations links you can click and check | ◐ | ◐ | ✓ |
| Transparency & safety research model cards, evals, known limits | ✓ | ◐ | ◐ |
| Enterprise controls (SSO, audit) retention policy, admin controls | ◐ | ✓ | ✓ |
| Strong document & data analysis read a paper, a dataset, a figure | ✓ | ✓ | ◐ |
| Native Docs / Drive / Sheets work where your files already live | ◐ | ◐ | ✓ |
✓ strong · ◐ partial · ✗ no · scores are qualitative